Claudia Mitchell and April Mandrona, eds., Our Rural Selves: Memory and the Visual in Canadian Childhoods
Bibliographic record
Abstract
rich, complex story is offered in an accessible and clearly organized narrative.Another contribution of the book lies in the explicit theoretical framing of the study.Scholarly academic audiences will appreciate the multiple theoretical lenses employed to make sense of the historical decision-making and the system level development of PSE in British Colombia.Within the three lenses, Cowin canvasses and critiques an array of theories that can be utilized to understand public policy.This expands the subsequent analysis and Cowin must be applauded for this important conceptual contribution to the PSE policy literature.While some readers may grapple with the range and complexity of the theoretical approaches reviewed, other readers may wish for a deeper analytical consideration of the data against fewer theories.Nevertheless, the author impressively balances breadth and depth across substantive content and theoretical analyses.Cowin provides a critical and informative study of public policy and structural development in British Columbia's postsecondary education system.Overall this book has much to offer a range of readers, including academics across disciplines (such as history, higher education, and public administration), policy makers, and graduate students.It is a welcome addition to the postsecondary history and policy literature.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".